Many contemporary businesses, including retail organizations, retail stores, wholesale distributors, manufacturing companies, and the like, perform periodic and ongoing strategic analysis as well as forecasting and automatic replenishment of their various business inventories and supplies in order to improve the efficiency and service levels of their operations. Such strategic forecasting and automatic replenishment systems help to manage inventories and supplies by predicting future throughputs, by quantifying anticipated depletion of raw and finished materials associated with those throughputs, and by quantifying the orders necessary to replenish depleted stocks. The strategic analysis, forecasting and automatic replenishment functions that these systems may perform can include: (1) predicting quantities and profit margins for sales over a specific period of time; (2) predicting the quantities of parts and upstream components that may be required to meet anticipated demand for certain finished goods scheduled to be completed or assembled during a specific period of time; (3) forecasting the lead time to supply materials necessary to meet anticipated demand for finished goods as well as component elements; and (4) predicting the specific demand periods when certain products will be needed. When these automated systems or processes are optimized, businesses may be better positioned to improve profits, increase efficiencies, and reduce waste.
As to specific categories of businesses, a retail mail order company, for example, may use automatic forecasting and replenishment (F&R) systems to stock the minimum amount of product necessary to supply anticipated demand, thereby reducing carrying costs, warehousing costs, and increasing customer satisfaction. As to brick and mortar retailers, a properly run forecasting and replenishment system can ensure that shelves are stocked with the appropriate merchandise to enhance sales and meet anticipated customer demand. Moreover, forecasting and replenishment systems help to ensure that low demand items are not over-bought, thereby minimizing the purchase of slow turnover items and their accompanying large storage costs and high return stock burdens. In each case, the profitability of a business may be optimized and business processes may run more efficiently when an accurate forecast and replenishment system is employed.
The goal of most retail business forecast and replenishment systems is therefore to provide for the automatic replenishment of goods in the right volume and at the right time with minimal human intervention in order to help optimize the profitability and efficiency of business operations. However, because business operations are not perfectly predictable, and because automated F&R processes are often not fully designed to handle each and every situation that may arise relating to the successful management of business inventories, automated forecasting and replenishment systems may generate business exceptions. An exception, in the context of forecasting and replenishment systems, may comprise a message describing a set of error conditions or attributes concerning a business operation. An exception is typically generated because an automated system has detected an error condition, but is unable or has been programmed not to resolve the error condition on its own. The exception is issued so that the associated error conditions and their attributes can be reviewed manually, and a solution can be selected, developed and/or initiated.
Forecasting and replenishment exceptions may cover all kinds of business exceptions, including administrative ones, that relate to a given business process. Depending on the type and size of a business, as well as many other factors, the number of automatically generated exceptions may be quite large. In most forecasting and replenishment systems, exceptions are displayed as transitory dialog messages, which, if not reviewed and handled immediately, are either overwritten by a new exception or they are queued for future review in the order in which they were generated. If a user who is viewing the transitory exception message is not qualified to respond to it, then the exception may go unresolved, either because it may be overwritten or because it may be too difficult to locate at a later time. Similarly, queued exceptions may also go unresolved, simply because of the difficulty in locating queued exceptions that match desired business characteristics, such as a user's area of expertise.
Accordingly, there is a need in the art for a system and method for storing, selecting, filtering, viewing and resolving exceptions generated by forecasting and replenishment processes and systems. Likewise, there is a need in the art for a system and method that will permit a business replenishment specialist who is trained in a specific business area to select, review and respond to filtered forecasting and replenishment exceptions according to the specialist's areas of responsibility and business interest. Additionally, there is a need in the art for a forecasting and replenishment system that automatically provides filtered access to stored business exceptions according to a user's predefined or selected business profile.